You cannot win the game but you can lose it
While AI can certainly be a competitive advantage, its
governance falls under the category of risk management. This means it has little to provide towards winning, but a big blunder can have enormous, potentially existential, impact on
a company.
Transparency
Transparency is key because transparency is instrumental for gaining the public’s
trust that AI is applied in a “good” way. Since AI governance offers little in
competitive advantage, openness is not going to hurt the bottom line.
Corporations and public debate
Cooperation cannot address AI governance in isolation. Many of
the questions need further elaboration by society and public debate. Even apparently
simple concepts such as fairness and non-bias are complex and need further
discussion.
Internal guidance and external oversight
Companies will need experts and executives, sufficiently
empowered, to govern the development of AI and provide concrete guidance to product
developers.
While a company’s board of directors may not have the
necessary expertise and experience in AI and its implication and risks, a specialized external advisory or supervisory board might be necessary. It will bring in additional expertise, will be
independent of company politics and will increase transparency resulting in
increased public trust.
Operational vs societal
The impact of AI on society is very broad and many topics
still need research and debate. Therefor it might be useful separating between
operational topics and societal challenges.
Operational topics are generally understood and typically
under company control, e.g. the quality of data, selection of algorithm by
their properties, e.g. explainability, or the design of AI enabled solution in
a way that the user is in control.
The governess of operational topics can be structured along
the following dimensions: data, algorithms, objective functions, policies and user
experience.
Societal challenges are much broader, have deeper impact on
society and are typically not under a company’s control. Examples include
future of work from a economic and a social perspective, wealth distributions
and the balance between privacy and safety and security
I will explore these questions in a separate blog post.
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